att_abstract={{Data fusion aims at resolving conflicts between different sources when 
integrating their data.  Recent fusion techniques find the truth by 
iterative MAP (Maximum A Posteriori) analysis that reasons about 
trustworthiness of sources and copying relationships between them. 
Providing explanations for such decisions is important, but can be 
extremely challenging because of the complexity of the analysis during 
decision making.

This paper proposes two types of explanations for data-fusion results: 
snapshot explanations target casual users, taking the provided data 
and any other decision inferred from the data as evidence; 
comprehensive explanations target advanced users, taking only the 
provided data as evidence.  We propose techniques that can efficiently 
generate correct and compact explanations. Experimental results show 
that (1) we generate correct explanations, (2) our techniques can
significantly reduce the sizes of the explanations, and (3) we can
generate the explanations efficiently.}},
	att_authors={ds8961, xd0649},
	att_categories={C_NSS.2, C_IIS.5},
	att_copyright={{International World Wide Web Conference Committee}},
	att_copyright_notice={{The definitive version was published in  2013. {{, 2013-05-10}}
	author={Divesh Srivastava and Xin Dong},
	institution={{International World Wide Web Conference - WWW 2013}},
	title={{Compact Explanation of Data Fusion Decisions}},